Likelihood to Recommend Quick dashboards from
Google Sheets - Easier to do the graphs than in
Google Sheets - Operational dashboards to be used in the day-to-day work - It is good both for retrospective data and to do a pulse check of the current status - Better for not giant amounts of data and not multiple data sources. - If you need a lot of graphs to be displayed on the same page, it can be a bit glitchy during configuration (then the use works fine).
Read full review If the person/ department does not have any knowledge in open source tools such as R, and Python. [Salesforce Einstein Analytics (formerly Wave Analytics)] could be a good option with no coding background required. However, if they have such human resource or can acquire these people, I would recommend open source tech and suggest not to use this tool.
Read full review Pros Filtering - you can filter across different dimensions and metrics to get a more specific "cut" of data Refreshing - data automatically ingests into Looker which allows reports to be updated and backfilled in real time Conditional Reporting - you can leverage Looker's reporting features to flag when a given metric or KPI falls below or above a specified threshold. For example, if you had a daily sales benchmark in a SAAS organization, you could use Looker to flag whenever daily sales falls above or below the benchmark Read full review Interactive Dashboards, it [consists] of wide variety of charts Data from different sources can be easily integrated with it Security, it provides easy way to secure and share the information with the users Support actions like opening hyperlink etc Almost everything can be done from configuration Data can easily be managed from dataflow. Read full review Cons Looker is less graphical or pictorial which makes it less attractive Consumes a lot of memory when there are multiple rows and columns, impacts performance too At times when we download huge chunks of raw data from Looker dashbords, the time taken to prepare the file is enormous - The user fails to understand if Looker has frozen or if the data is getting prepared in the background for downloading. In turn, user ends up triggering multiple downloads Read full review Implementation takes time and resources. It is a heavy lift to implement and at first, it can take a little bit of time to understand what you are looking at. But once it's implemented it's easy to get started. Without any BI expertise or resources available to your organization, the implementation of this is difficult. If you aren't used to BI tools and don't have an expert in house, the terminology can be difficult to understand at first. Their support is not on hand to help you if you encounter any issues, at least not on all the plans or the basic plans. Real-time support service is an add-on, so you'll need to be patient if you require help or pay extra money. More functionality for the tool is needed to compete with other heavyweights in the arena like Tableau, Qlik, and Microstrategy. Still lacks the robustness, functionality, and flexibility other competing products possess. Read full review Likelihood to Renew We've been very happy with Looker so far, and all teams in the organization are starting to see its value, and use it on a frequent basis. It has quickly become our accessible "source of truth" for all data/metrics.
Read full review Usability Looker is relatively easy to use, even as it is set up. The customers for the front-end only have issues with the initial setup for looker ml creations. Other "looks" are relatively easy to set up, depending on the ETL and the data which is coming into Looker on a regular basis.
Read full review Overall usability is absolutely worth the price. It help me to save tons of time working on raw data in Excel file. It also minimize the discrepancy in data format when there are multiple user inputting the data. Every data inputted in Salesforce is standardized, therefore it is very easy to keep track / generating performance report even though you are having more than 20 projects recorded in Salesforce Einstein Analytics.
Tony Phan Tactical Procurement Specialist (Vietnam & APAC Support) - Source To Procure Team
Read full review Support Rating Never had to work with support for issues. Any questions we had, they would respond promptly and clearly. The one-time setup was easy, by reading documentation. If the feature is not supported, they will add a feature request. In this case, LDAP support was requested over OKTA. They are looking into it.
Read full review I have not come across any bad experiences with the support provided. Also, I observed regular updates have been implemented without breaking the tool. But in my opinion, Now Tableau CRM has huge market challenges with tools like Power BI and its spread
Read full review Implementation Rating An implementation partner would certainly result in greater output in a more efficient amount of time. However, I have found implementation partners to be extremely expensive for the output received (at least working for a non-profit company they are frequently unaffordable). Internal implementation does help with usable output though since internal knowledge would better know the data architecture and business processes
Read full review Alternatives Considered Looker is an off-the-shelf, free tool for Google business users. Other than the internal cost of time to build, we had no costs to set up what we needed to do. Knowledge sharing internally and using templates greatly reduced this cost, making the overall cost very low.
Read full review Tableau is the absolute top of the class when it comes to business intelligence, but it doesn't make sense for every business case. In our case, we needed a simple data visualization platform for our CRM platform and sales pipeline. Salesforce Analytics, while nowhere near as robust, did the job we needed it to do perfectly in a significantly more cost-effective manner.
Read full review Return on Investment Allowing others to self-serve their own analytics and connect it to Looker simply and easily has helped unblock the central data team so they can instead focus on validated dashboards whilst stakeholders manage their day-to-day analysis themselves. Countless engineering hours have been freed up by not having to manage every user permission for each BI tool; we have a BYOBI approach; Bring Your Own BI Creation and management of a semantic layer (LookML =Looker Modeling Language ) allows peoples sandboxes and production databases to become clutter free. Minor adjustments, conditional fields, and even some modelling can all be done in LookML which doesn't need oversight or governance from the central data team. LookML, specifying drilldown fields and their sub-queries, as well as generally creating dynamic parameters with Liquid are all great features, but can have a steep learning curve. it may take some time to understand how to create this middle layer correctly, or even pose a risk of inheriting complex code from another source which can be unmaintainable if it becomes too big. Some level of governance is recommended if Looker is used by a large number of editors. Read full review Absolutely a must-have tool if you are working on saving project Create a centralized database to track project target across region Easily create chart to showcase data / performance Tony Phan Tactical Procurement Specialist (Vietnam & APAC Support) - Source To Procure Team
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